When users look for information, using search engines, they get a list of what seems relevant to the search engine.
However, the choice of a search query used for executing a search, by an individual user, is not necessarily the same as the search query choice of another user, even though both are trying to find the same information. Thus, in most cases, a user ends up with a list of primary search results, which he or she then uses as a base for reaching relevant documents.
The final set of relevant documents may contain documents which are not included in the search results. This happens when a user reads a first (primary) document and then opens a secondary document from links found in the primary document.
This process can continue for a long time wherein more documents are opened from links found in previously opened documents. Some documents are kept open or saved while others are closed as they are found to be not relevant.
The issue is, that when a user executes the same (or very similar) search query again, at a later time, said user will have to go through the same tedious research process once more, trying to generate the same list.
One solution is for users to organize search results manually, creating a list of documents relevant to a particular topic and ordering them according to their relevancy. However, many times, such investment in time does not seem relevant when first executing the search. Only when the same information is needed again in a later time, does a user regret not making the effort.
Patent application publication 20070088692 discloses several methods for making search results more relevant to a user or a group of users. However, such methods only apply to documents listed in the primary search results. They do not deal with the end result—being the list of documents a user has built, pursuant to receiving the ones listed in the search results.
Thus, it would be beneficial if users had the option of automatically retrieving the list of documents they themselves found relevant when they executed a similar search in the past. Further, it would be advantageous if classifying a set of documents as relevant is performed automatically by software monitoring behavior of said users.